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In this paper, we study the quantitative role of productivity differences in explaining migration in presence of multiple destination choices. We construct a dynamic general equilibrium model with multi-region, multi-sector set-up where labor is a mobile input, which adjusts to regional and sectoral productivity shocks, resulting in migration across regions. The proposed model generates a migration network where the flow of migrants between any two regions follows a gravity equation. We calibrate the model to the U.S. data and we find that variation in industrial and regional total factor productivity shocks explains about 63% of the interstate migration in the U.S. Finally, we perform comparative statics to estimate the effects of long-run structural changes on migration. We find that capital intensity of the production process and the demand for services over manufactured goods negatively impact aggregate level of migration whereas asymmetries in trade patterns do not appear to have substantial effects.

Immobility puzzle in the European Union (EU) takes the form of observed level of migration within the EU being substantially less than what is expected in a union allowing free labor mobility. We use a dynamic general equilibrium model of migration in a multi-region setting with heterogeneity in sectoral compositions, productivity and endowments of productive inputs, to construct a flow network of migrants (Chakrabarti and Sengupta, Econ. Model. 61:156–168 (2017)) ([7], Economic Modelling). When tested on the US data which we consider to be a benchmark for institutional homogeneity compared to Europe, this model explains substantial part of the variation in both the nominal and relative flows of state-to-state migration under suitable calibration. On the other hand, this model explains the relative flow network of the EU well but predicts a higher nominal flow than is seen in the data, thus illustrating and quantifying the puzzle. Following the hypothesis that institutional heterogeneity across the EU countries induces frictions on such labor reallocation process, we use dyadic regression to analyze the effects of pair-wise institutional distances which capture a broad spectrum of socio-cultural and political differences between countries, on the estimated missing mass of migrants. Linguistic differences appear to be the key factor explaining the missing mass of migrants.

We consider the problem of testing for a structural break in the spatial lag parameter in a panel model (spatial autoregressive). We propose a likelihood ratio test of the null hypothesis of no break against the alternative hypothesis of a single break. The limiting distribution of the test is derived under the null when both the number of individual units N and the number of time periods T is large or N is fixed and T is large. The asymptotic critical values of the test statistic can be obtained analytically. We also propose a break-date estimator that can be employed to determine the location of the break point following evidence against the null hypothesis. We present Monte Carlo evidence to show that the proposed procedure performs well in finite samples. Finally, we consider an empirical application of the test on budget spillovers and interdependence in fiscal policy within the U.S. states.

NEED FOR EIA: Environment and development are not exclusive of one another but are complimentary and dependent on each other. Environment is where we live and development is what we do to improve that living. “Development”, the word is very contradictory. It has both negative and positive aspects attached to it. Development on one hand leads to advancement (i.e. technological, social) which is the “Positive aspect of Development”. It is a pre-requisite for advancement in every sphere of life but it is being evident that development always takes place at the cost of the environment. Thus this is termed as the “Negative aspect of Development”. The world is facing several environmental problems related to technological and industrial development as well as a rapid population growth which has, but tremendous amount of strain on the environmental resources. The Per Capita Ecological Footprints exceed the earth’s biological capacity by about 20%. Thus there is an urgent need for striking a balance between the capacity of the environment and the quantum of development. And as we all aim towards sustainable development, it is necessary to evaluate the impact of all development proposal on the environment. Development is quoted as essential to improve the quality of life. Therefore to have development it was realized that it should be accompanied with sustainable ways so as to reduce the impact of it on the environment. One such effective way is to carry out “ENVIRONMENTAL IMPACT ASSESSMENT” of all proposed projects.